Marie Fridberg

The Thermography studies will investigate how we can detect and monitor early signs of infection before the patient develops symptoms and how can we use the discipline of thermography evidence based in clinical practice. The aim is to improve postsurgical care for patients and avoid complications of surgery.

It might even be possible to monitor patients outside the hospital using small thermographic cameras that can be added on to a mobile phone. If thermography can be used as an adjunct tool to improve surveillance from the patient's home setting, then we can minimize follow-up visits to the outpatient clinic and avoid unnecessary time and resources for both the patient and the healthcare system.

This project will generate a huge amount of precise data, a unique and well-suited base to work with machine learning and AI solutions. The political tendency is that health data will be used to develop AI solutions in healthcare – maybe not in an evidence-bases and rational way though - we clinicians need to devote ourselves to this innovative process and keep our focus on a clinically intelligent way of learning and securing an evidence-based introduction of AI into clinical practice.

The setup is multidisciplinary international cross-sectional studies. The Thermography studies will focus on orthopedic patients with external frames. These patients are at considerable risk of infection during the treatment period of several months, and an infection can in the worst case scenario be limb threatening. The experience and knowledge we obtain from this project can be used in general to improve care for patients after surgery in the future.

The Thermography studies are part of the Clinical Intelligence project – a new innovative solution to care for post-surgical patients with new technology equipment and evidence based use of AI In health care.